Fix audio feature extractor deps (#24636)

* Fix audio feature extractor deps

* use audio utils window over torch window

tests/models/encodec/test_feature_extraction_encodec.py

@@ -20,16 +20,13 @@ import unittest
 
 import numpy as np
 
-from transformers import is_speech_available
+from transformers import EncodecFeatureExtractor
 from transformers.testing_utils import require_torch
 from transformers.utils.import_utils import is_torch_available
 
 from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
 
 
-if is_speech_available():
-    from transformers import EncodecFeatureExtractor
-
 if is_torch_available():
     import torch
 
@@ -103,7 +100,7 @@ class EnCodecFeatureExtractionTester(unittest.TestCase):
 
 @require_torch
 class EnCodecFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
-    feature_extraction_class = EncodecFeatureExtractor if is_speech_available() else None
+    feature_extraction_class = EncodecFeatureExtractor
 
     def setUp(self):
         self.feat_extract_tester = EnCodecFeatureExtractionTester(self)

tests/models/mctct/test_feature_extraction_mctct.py

@@ -20,15 +20,12 @@ import unittest
 
 import numpy as np
 
-from transformers import is_speech_available
+from transformers import MCTCTFeatureExtractor
 from transformers.testing_utils import require_torch
 
 from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
 
 
-if is_speech_available():
-    from transformers import MCTCTFeatureExtractor
-
 global_rng = random.Random()
 
 
@@ -102,7 +99,7 @@ class MCTCTFeatureExtractionTester(unittest.TestCase):
 
 @require_torch
 class MCTCTFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
-    feature_extraction_class = MCTCTFeatureExtractor if is_speech_available() else None
+    feature_extraction_class = MCTCTFeatureExtractor
 
     def setUp(self):
         self.feat_extract_tester = MCTCTFeatureExtractionTester(self)

tests/models/speecht5/test_feature_extraction_speecht5.py

@@ -20,16 +20,13 @@ import unittest
 
 import numpy as np
 
-from transformers import BatchFeature, is_speech_available
+from transformers import BatchFeature, SpeechT5FeatureExtractor
 from transformers.testing_utils import require_torch
 from transformers.utils.import_utils import is_torch_available
 
 from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
 
 
-if is_speech_available():
-    from transformers import SpeechT5FeatureExtractor
-
 if is_torch_available():
     import torch
 
@@ -142,7 +139,7 @@ class SpeechT5FeatureExtractionTester(unittest.TestCase):
 
 @require_torch
 class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
-    feature_extraction_class = SpeechT5FeatureExtractor if is_speech_available() else None
+    feature_extraction_class = SpeechT5FeatureExtractor
 
     def setUp(self):
         self.feat_extract_tester = SpeechT5FeatureExtractionTester(self)

tests/models/tvlt/test_feature_extraction_tvlt.py

@@ -22,7 +22,7 @@ import unittest
 
 import numpy as np
 
-from transformers import is_datasets_available, is_speech_available
+from transformers import TvltFeatureExtractor, is_datasets_available
 from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
 from transformers.utils.import_utils import is_torch_available
 
@@ -35,9 +35,6 @@ if is_torch_available():
 if is_datasets_available():
     from datasets import load_dataset
 
-if is_speech_available():
-    from transformers import TvltFeatureExtractor
-
 global_rng = random.Random()
 
 
@@ -111,7 +108,7 @@ class TvltFeatureExtractionTester(unittest.TestCase):
 @require_torch
 @require_torchaudio
 class TvltFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.TestCase):
-    feature_extraction_class = TvltFeatureExtractor if is_speech_available() else None
+    feature_extraction_class = TvltFeatureExtractor
 
     def setUp(self):
         self.feat_extract_tester = TvltFeatureExtractionTester(self)